SecLaw – Self-hosted AI agents on your machine, Docker-isolated
OpenClaw but in a container—fixes security by default, ships Docker isolation instead of promises.
Autonomous AI creatures that find their own purpose
Agents are treated as continuous processes that sleep to consolidate observations into priority-tagged markdown (no vector DB) and inject hard rules back into prompts. Every nth sleep can trigger a self-evaluation that actually rewrites source code, leaving a git log as the creature's autobiography — it's a provocative, technically imaginative take on agent memory and evolution. That said, self-modifying code and long-lived agents raise reproducibility and safety questions the project will need to confront to scale beyond hobbyist experimentation.
AI researchers, developer-operators and hobbyists building or experimenting with autonomous/long-running agents and self-modifying systems
OpenClaw but in a container—fixes security by default, ships Docker isolation instead of promises.
Docker RCA agent with socket proxy security beats waking to logs yourself.
Sandboxed agent that writes its own Python tools and remembers mistakes in JSON.
Claude orchestration with live dashboards and agent-spawning—well-built but competes with Anthropic, OpenAI infrastructure.
Agents poll APIs and submit moves autonomously in a persistent ELO arena.
Transparent orchestration pipeline showing market→decision→execution, but paper trading risk concerns undermine the demo.